Qinghua Wang

2.1k total citations · 1 hit paper
59 papers, 1.5k citations indexed

About

Qinghua Wang is a scholar working on Molecular Biology, Epidemiology and Materials Chemistry. According to data from OpenAlex, Qinghua Wang has authored 59 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 27 papers in Epidemiology and 16 papers in Materials Chemistry. Recurrent topics in Qinghua Wang's work include Protein Structure and Dynamics (27 papers), Enzyme Structure and Function (16 papers) and Influenza Virus Research Studies (14 papers). Qinghua Wang is often cited by papers focused on Protein Structure and Dynamics (27 papers), Enzyme Structure and Function (16 papers) and Influenza Virus Research Studies (14 papers). Qinghua Wang collaborates with scholars based in United States, China and Australia. Qinghua Wang's co-authors include Jianpeng Ma, Fengyun Ni, Tian Xia, Zhiliang Wang, Mingyang Lu, Elena Kondrashkina, Lin Li, Jingyue Bao, Xiaodong Wu and Jun Shen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and The Journal of Chemical Physics.

In The Last Decade

Qinghua Wang

56 papers receiving 1.5k citations

Hit Papers

Molecular Characterization of African Swine Fever Virus, ... 2018 2026 2020 2023 2018 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Qinghua Wang United States 22 659 597 446 364 281 59 1.5k
Jingfei Wang China 18 209 0.3× 218 0.4× 350 0.8× 305 0.8× 205 0.7× 53 1.0k
Geoff Sutton United Kingdom 23 846 1.3× 138 0.2× 274 0.6× 702 1.9× 399 1.4× 41 2.0k
Claudine Porta United Kingdom 22 881 1.3× 224 0.4× 267 0.6× 467 1.3× 106 0.4× 26 2.0k
Takeshi Haga Japan 20 576 0.9× 456 0.8× 183 0.4× 305 0.8× 130 0.5× 102 1.6k
Jonathan M. Diprose United Kingdom 14 755 1.1× 130 0.2× 189 0.4× 721 2.0× 279 1.0× 16 1.7k
Hélène Dutartre France 26 669 1.0× 270 0.5× 377 0.8× 716 2.0× 312 1.1× 54 2.3k
Robyn Malby Australia 14 576 0.9× 138 0.2× 151 0.3× 349 1.0× 240 0.9× 17 1.2k
Huaguang Lu United States 25 759 1.2× 471 0.8× 229 0.5× 892 2.5× 38 0.1× 53 1.8k
Hélène Malet France 22 768 1.2× 438 0.7× 52 0.1× 1.1k 2.9× 111 0.4× 32 2.5k
Stéphane Bressanelli France 29 1.1k 1.7× 1.5k 2.4× 85 0.2× 1.3k 3.5× 108 0.4× 71 3.9k

Countries citing papers authored by Qinghua Wang

Since Specialization
Citations

This map shows the geographic impact of Qinghua Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Qinghua Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qinghua Wang more than expected).

Fields of papers citing papers by Qinghua Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Qinghua Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Qinghua Wang. The network helps show where Qinghua Wang may publish in the future.

Co-authorship network of co-authors of Qinghua Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Qinghua Wang. A scholar is included among the top collaborators of Qinghua Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Qinghua Wang. Qinghua Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
Xu, Gang, et al.. (2024). OPUS-Rota5: A highly accurate protein side-chain modeling method with 3D-Unet and RotaFormer. Structure. 32(7). 1001–1010.e2. 1 indexed citations
3.
Liu, Wenlian, et al.. (2024). Comparative study on convolutional neural network and regression analysis to evaluate uniaxial compressive strength of Sandy Dolomite. Scientific Reports. 14(1). 9880–9880. 5 indexed citations
4.
Wang, Qinghua, et al.. (2021). OPUS-Rota4: a gradient-based protein side-chain modeling framework assisted by deep learning-based predictors. Briefings in Bioinformatics. 23(1). 13 indexed citations
5.
Wang, Qinghua, et al.. (2020). OPUS-Fold: An Open-Source Protein Folding Framework Based on Torsion-Angle Sampling. Journal of Chemical Theory and Computation. 16(6). 3970–3976. 6 indexed citations
6.
Xu, Gang, et al.. (2019). OPUS‐SSF: A side‐chain‐inclusive scoring function for ranking protein structural models. Protein Science. 28(6). 1157–1162. 5 indexed citations
7.
Zeng, Jia, et al.. (2018). Three classes of response elements for human PRC2 and MLL1/2–Trithorax complexes. Nucleic Acids Research. 46(17). 8848–8864. 8 indexed citations
8.
Ni, Fengyun, Elena Kondrashkina, & Qinghua Wang. (2017). Determinant of receptor-preference switch in influenza hemagglutinin. Virology. 513. 98–107. 11 indexed citations
9.
Bao, Jingyue, Qinghua Wang, Lin Li, et al.. (2017). Evolutionary dynamics of recent peste des petits ruminants virus epidemic in China during 2013–2014. Virology. 510. 156–164. 28 indexed citations
10.
Ni, Fengyun, Elena Kondrashkina, & Qinghua Wang. (2015). Structural and Functional Studies of Influenza Virus A/H6 Hemagglutinin. PLoS ONE. 10(7). e0134576–e0134576. 28 indexed citations
11.
Ni, Fengyun, Innocent N. Mbawuike, Elena Kondrashkina, & Qinghua Wang. (2013). The roles of hemagglutinin Phe-95 in receptor binding and pathogenicity of influenza B virus. Virology. 450-451. 71–83. 18 indexed citations
12.
Ni, Fengyun, Elena Kondrashkina, & Qinghua Wang. (2013). Structural basis for the divergent evolution of influenza B virus hemagglutinin. Virology. 446(1-2). 112–122. 50 indexed citations
13.
Liu, Hualei, Yan Lv, Weijian Huang, et al.. (2010). [Detection of molecular markers of amantadine resistance in swine influenza viruses by pyrosequencing].. PubMed. 50(3). 395–9. 2 indexed citations
14.
Wang, Liang, Juan Cheng, Rui Liu, et al.. (2009). Peptide corresponding to the C terminus of tissue factor pathway inhibitor inhibits mesangial cell proliferation and activation in vivo. Peptides. 30(12). 2330–2336. 5 indexed citations
15.
Shen, Jun, Jianpeng Ma, & Qinghua Wang. (2009). Evolutionary Trends of A(H1N1) Influenza Virus Hemagglutinin Since 1918. PLoS ONE. 4(11). e7789–e7789. 66 indexed citations
16.
Shen, Jun, et al.. (2008). Diversifying selective pressure on influenza B virus hemagglutinin. Journal of Medical Virology. 81(1). 114–124. 41 indexed citations
17.
Chen, Xiaorui, Billy K. Poon, Athanasios Dousis, Qinghua Wang, & Jianpeng Ma. (2007). Normal-Mode Refinement of Anisotropic Thermal Parameters for Potassium Channel KcsA at 3.2 Å Crystallographic Resolution. Structure. 15(8). 955–962. 28 indexed citations
18.
Chen, Jiming, Meng Yu, Chris Morrissy, et al.. (2006). A comparative indirect ELISA for the detection of henipavirus antibodies based on a recombinant nucleocapsid protein expressed in Escherichia coli. Journal of Virological Methods. 136(1-2). 273–276. 28 indexed citations
19.
Wang, Xijun, Jinying Ge, Sen Hu, et al.. (2006). Efficacy of DNA Immunization with F and G Protein Genes of Nipah Virus. Annals of the New York Academy of Sciences. 1081(1). 243–245. 21 indexed citations
20.
Wu, Yinghao, Tian Xia, Mingyang Lu, et al.. (2005). Folding of Small Helical Proteins Assisted by Small-Angle X-Ray Scattering Profiles. Structure. 13(11). 1587–1597. 24 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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